Larger companies face the problem of large numbers of incoming documents, binding significant resources in reading and redirecting to the corresponding sections. In this presentation an approach is presented, which discusses the solution regarding incoming emails at ERGO Nuremberg. Approx. 1k emails receives this location per day, which were manually read and redirected. Expecting an estimated increase of the email rate, a solution based on current machine learning approaches has to be implemented to support the company. This talk will cover the data preparation, the architecture and the final operationalization of this model in detail. The additional challenges of data science in the field of insurances regarding data protection law will be discussed as well as the technical requirements and boundaries as well as the usual pitfalls.